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Salesforce

Data Engineer (SMTS / LMTS) - MDM

  • Office
  • 6+ years

Salary

Not stated

Similar roles pay $190K - 230K a year · our estimate

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Description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the 1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

The Experience

Salesforce is building the most comprehensive understanding of business relationships across our global customer ecosystem. A critical pillar of this effort is Master Data Management (MDM): the systems that identify, enrich, deduplicate, and govern every business entity and corporate hierarchy we interact with.

We are seeking talented engineers at the Senior Member of Technical Staff (SMTS) and Lead Member of Technical Staff (LMTS) levels to join our MDM Engineering organization. In these roles, you will design, develop, and operate critical MDM capabilities — including entity resolution, golden record management, corporate hierarchy automation, and enterprise data integration solutions — while leveraging modern AI technologies to build developer tools, engineering automation, and productivity accelerators across the MDM ecosystem.

At the LMTS level, you will drive technical strategy, architect end-to-end platforms, and provide cross-functional leadership. At the SMTS level, you will serve as a hands-on technical leader with a bias for action, translating architecture into scalable, production-grade systems. Both roles partner closely with Product Management, Data Governance, Architecture, Systems Integrator partners, and downstream consuming teams.

What You'll Actually Be Doing

Design, develop, and maintain AI-powered developer tools, engineering automation, and productivity accelerators using modern AI platforms such as Claude, Cursor, Windsurf, GitHub Copilot, and related technologies

Build and maintain end-to-end MDM integration systems, including MuleSoft integrations, Airflow-based workflows, API orchestration layers, event-driven architectures, Change Data Capture (CDC), and batch processing pipelines

Implement entity resolution, golden record lifecycle management, hierarchy processing, data quality validation, and governance capabilities

Build and maintain integrations with third-party data providers such as Dun & Bradstreet, Moody's, and Leadspace to support data enrichment and corporate hierarchy management

Design and optimize data models, database schemas, APIs, and integration patterns supporting MDM business requirements across hierarchical, relational, and party data structures

Build production-grade solutions with strong monitoring, alerting, operational supportability, and security by design

Drive adoption of AI-assisted software engineering practices to improve developer productivity, testing efficiency, and delivery speed

Participate in design reviews, code reviews, operational readiness reviews, and release activities

Troubleshoot complex production issues, drive root cause analysis, and implement scalable long-term solutions

Collaborate effectively with globally distributed teams across multiple time zones

LMTS additionally:

Architect and evolve end-to-end MDM integration systems and define technical strategy for entity resolution, golden record lifecycle, hierarchy management, data quality, and governance across multiple business domains

Lead design reviews and establish engineering standards for scalability, observability, resiliency, security, testing, and operational excellence

Partner with PMTS, Product Owners, TPMs, and business stakeholders to define architecture, roadmap priorities, solution designs, and delivery plans aligned with business objectives

Provide technical leadership across internal engineering and systems integrator teams

You're Our Person If...

Minimum Qualifications — SMTS (8+ years experience):

8+ years of experience in software engineering, data engineering, enterprise integration, or MDM platforms

Proven experience leveraging modern AI-assisted development platforms (Claude, Cursor, Windsurf, GitHub Copilot, or similar) to improve engineering productivity

Strong understanding of Generative AI and agentic workflows and their practical application within software engineering organizations

Strong hands-on experience with Informatica SaaS MDM , particularly with party data models including Account, Contact, Organization, and Supplier

Strong hands-on development experience with Java, REST APIs, microservices, and enterprise integration patterns

Experience building MuleSoft integrations, API orchestration services, Airflow workflows, ETL/ELT pipelines, and large-scale data engineering solutions

Experience with Kafka or similar event-streaming technologies, CDC, and event-driven architectures

Experience with AWS, GCP, or Azure cloud services and cloud-native application development

Strong knowledge of SQL, data modeling, database design, and distributed data processing architectures

Excellent communication and collaboration skills

A related technical degree required

Minimum Qualifications — LMTS (10+ years experience):

10+ years of progressive experience in enterprise integration, data engineering, MDM, or large-scale data platform development

Deep expertise in MDM concepts including entity resolution, golden record lifecycle, match/merge/survivorship, data quality, governance, and hierarchy management

Proven experience designing and building API orchestration layers, MuleSoft integrations, microservices, and event-driven architectures

Proven experience building developer tools using modern AI tech stack like Claude, Cursor etc. in MDM domain.

Demonstrated technical leadership, cross-functional collaboration, and ability to drive multiple complex initiatives from design through delivery

Excellent communication skills with the ability to influence stakeholders across all levels of the organization

A related technical degree required

Even Better If...

Experience with Salesforce Data Cloud, CRM platforms, or broader Salesforce ecosystem technologies

Experience working with corporate hierarchy data from Dun & Bradstreet, Moody's, or Leadspace, including family tree traversal, DUNS resolution, monitoring, and registration workflows

Experience building Python-based data engineering frameworks and automation solutions

Experience with data stewardship, governance processes, and operational data quality tooling

Experience with Retrieval-Augmented Generation (RAG), vector databases, AI agents, MCP frameworks, or related AI technologies

Experience building internal developer platforms, engineering productivity tools, or agentic solutions supporting enterprise engineering teams

Demonstrated track record of driving measurable engineering productivity improvements through AI-enabled tooling and automation

Certifications in MDM, data management, cloud platforms, MuleSoft, Informatica, or related technologies

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Where you’d work

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About the company

Salesforce

  • Industry: SaaS

Offices in San Francisco, United States, New York, United States, Seattle, United States, United States

Also hiring in Chicago, United States, Atlanta, United States, Dallas, United States and 32 more places

55 of their 340 open roles are remote

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  • Your field
  • Level
  • Stack
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  • Must-haves
Details11 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • SQL
  • AWS
  • Kafka
  • Azure
  • Airflow
  • LLMs
  • RAG
  • Vector databases
Type
Full-time
Industry
SaaS
Specialty
Data Engineering
Region
United States
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Engineering
Experience
8+ years
Tech stack
  • Python
  • SQL
  • AWS
  • Kafka
  • Azure
  • Airflow
  • LLMs
  • RAG
  • Vector databases

Location

Work model
Office
Region
United States
Offices
  • San Francisco, United States
  • New York, United States
  • Seattle, United States
  • United States

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Company

Industry
SaaS

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